DOCSLIB.ORG

Long-Term Trends of Instability and Associated Parameters Over The

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Long-Term Trends of Instability and Associated Parameters Over The 1 Long-term trends of instability and associated parameters 2 over the Indian region obtained using radiosonde network 3 Rohit Chakraborty, Madineni Venkat Ratnam* and Shaik Ghouse Basha 4 National Atmospheric Research Laboratory, India. 5 Correspondence to: M. Venkat Ratnam ([email protected]) 6 7 Abstract 8 Long-term trends of the parameters related to convection and instability obtained from 27 radiosonde 9 stations across 6 sub-divisions over the Indian region during the period 1980-2016 is presented. A total of 16 10 parcel and instability parameters along with moisture content, wind shear, and thunderstorm and rainfall 11 frequencies have been utilized for this purpose. Robust fit regression analysis is employed on the regional 12 average time series to calculate the long-term trends on both seasonal and yearly basis. The Level of Free 13 Convection (LFC) and Equilibrium Level (EL) height is found to ascend significantly in all Indian sub- 14 divisions. Consequently, the coastal regions (particularly the western coasts) experience increasing in Severe 15 Thunderstorm (TSS) and Severe Rainfall Frequencies (SRF) in the pre-monsoon while the inland regions 16 (especially central India) experience an increase in Ordinary Thunderstorm (TSO) and Weak Rain Frequency 17 (WRF) during the monsoon and post-monsoon. The 16-20 year periodicity is found to dominate the long-term 18 trends significantly compared to other periodicities and the increase in TSS, and Convective Available Potential 19 Energy (CAPE) is found more severe after the year 1999. The enhancement in moisture transport and associated 20 cooling at 100 hPa along with dispersion of boundary layer pollutants is found to be the main cause for the 21 increase in CAPE which leads to more convective severity in the coastal regions. However, in inland regions 22 moisture-laden winds are absent and the presence of strong capping effect of pollutants on instability in the 23 lower troposphere has resulted in more Convective Inhibition Energy (CINE). Hence, TSO and weak rainfall 24 occurrences have increased particularly in these regions. 25 Key words: Instability, Convection, Long-term trends, Radiosonde 26 27 1. Introduction 28 Intense convective phenomena are a common climatic feature in the Indian tropical region which occurs 29 during the pre-monsoon to post-monsoon seasons (April–October) (Ananthakrishnan, 1977) and they are 30 generally accompanied by intense thunderstorms, lightning, wind gusts with heavy rainfall. Hence, they are 31 known to induce immense socio-economic hazards including loss of life and property. Several reports have 32 shown an increase in the climatic extreme occurrence and intensity of these phenomena throughout the world 33 (Webster et al., 2005; Emanuel, 2006). In this connection, the traditional surface-based parcel theory has been 34 utilized to understand convective processes using atmospheric soundings as it calculates the atmospheric 35 instabilities and other parameters at various heights (Huntrieser et al., 1997; Santhi et al., 2014; Nelli et al, 36 2018a). 1 37 Considering the importance of studying the long-term trends in climatic extremes, a series of research 38 attempts have been orchestrated world-wide in the last two decades. Using multiple tropical stations and re- 39 analysis data, Gettleman et al. (2002) and Riemann-Campe et al. (2009) have shown that Convective Available 40 Potential Energy (CAPE) has been increasing very strongly with a growth rate of ~20% per decade during the 41 period 1958-1997 due to increase in surface heating and moisture. Gensini and Mote (2015) projected a 236 % 42 increase in severe thunderstorm frequency from 1980-1990 to 2080-2090 over the eastern United States (US). 43 Further, Brooks (2013) used various combinations of CAPE and Vertical Wind Shear (VWSH) products and 44 results hinted towards a probable increase in the severe thunderstorms over the US. It was also observed that the 45 effect of increasing CAPE is more dominant on convective severity than in case of decreasing shear. On the 46 other hand, studies by Prein et al. (2017) showed that a recent increase of temperature has led to a rise of 47 moisture ingress and consequently the frequency and severity of extreme precipitation events associated with 48 intense convection have shown a steep rise everywhere in the world. At the same time, an increase in 49 thunderstorm severity and instability has also been reported by many attempts over the Asian region (Wang et 50 al., 2011; Saha et al., 2017). 51 Over the Indian region, Manohar et al. (1999) studied the latitudinal variation and distribution of 52 thunderstorm frequency and CAPE over 78 Indian stations during 1970-1980 and they postulated that the 53 ambient temperature at 100 hPa pressure level has a strong relationship with it. Dhaka et al. (2010) utilized 54 radiosonde observations during 1958-1997 and obtained very prominent anti-correlations on both yearly and 55 seasonal basis between convection strength (CAPE) and upper troposphere temperatures at 100 hPa (T100). 56 Later, Murugavel et al. (2012) studied the long term trends of CAPE from 32 radiosonde stations during 1984- 57 2008 and revealed an alarming growth in monsoon CAPE over India with a slope of 38 J/kg/year. However, 58 they additionally stated that the low-level moisture and solar cycle can have additional impact on the increasing 59 CAPE. Recently from reanalysis datasets, Chakraborty et al. (2017a) and Saha et al. (2017) reported that lower 60 lower tropospheric instability is reducing over few Indian stations after 1980 due to increasing levels of 61 pollution. Apart from that, some studies have also attempted to correlate convective severity with boundary 62 layer phenomena, surface fluxes, solar effect and precipitation; (Murthy and Sivaramakrishnan, 2006; 63 Allappattu and Kunnikrishnan, 2009; Xie et al., 2011, Nelli et al. 2018b). 64 Previous studies over India have shown the distribution of CAPE only whereas other parameters like 65 Convective Inhibition Energy (CINE), Mixed Layer CAPE (MLC), Lifted Index (LI), Total Totals Index (TTI), 66 and Precipitable Water Vapor (PWV) are also important as they explain how the atmospheric instability and 67 moisture changes at various levels of the atmosphere. In addition, the influence of climatic oscillation (Quasi- 68 Biennial Oscillation (QBO), El-Nino Southern Oscillation (ENSO) and Solar Cycle) on the seasonal and annual 69 variation of convective parameters was also not studied in detail. Therefore in the present study, long-term 70 variation of parcel parameters (Lifted Condensation Level (LCL), Level of Free Convection (LFC), Equilibrium 71 Level (EL), CAPE and CINE), with instability (LI, Vertical Totals Index (VT)), moisture (PWV, and PWV at 72 low levels (PWL)), thunderstorm and rainfall severity frequencies (Thunderstorm-Severe (TSS), Thunderstorm- 73 Ordinary (TSO), Weak Rain Fall (WRF) and Strong Rain Fall (SRF)) followed by Temperature at 100hPa 74 (T100) and Wind Shear (WSH) is investigated using 27 radiosonde stations along with gridded rainfall data over 75 India. This article is structured as follows: Section 2 describes the datasets and methodology adopted for the 76 present study. Section 3 presents the long-term analysis of parcel and instability parameter over Chennai 2 77 (13.08oN, 80.27oE) and 6 sub-divisions of the Indian subcontinent on both annual and seasonal basis, followed 78 by the periodicity and split trend analysis. Finally, a discussion on the results and conclusions is appended in 79 Section 4 and 5, respectively. 80 81 2. Dataset and Methodology 82 Radiosonde observations from 27 stations over the Indian region from 1980-2016 are obtained from 83 Integrated Global Radiosonde Archives (https://www1.ncdc.noaa.gov/pub/data/igra/derived/derived-por/). 84 These datasets provide daily temperature and humidity profiles from 1538 stations around the world in fixed 85 pressure levels after doing quality checks (Durre et al., 2006; Ferreira et al. 2018). These studies have concluded 86 that the radiosonde data quality from IGRA has faced certain problems from time to time, but such cases are not 87 so prominent over the Indian region, especially after the year 1980. It is mainly because of the higher accuracy 88 and reliability of this in-situ measurement technique that these datasets are widely used worldwide nowadays for 89 calibrating other continuous profiler instruments (Chakraborty and Maitra, 2016). In accordance with data 90 availability and reliability, only 27 stations have been considered out of 37 IGRA Indian radiosonde stations 91 thereby providing descent data availability for carrying out this study. When an in depth investigation is done on 92 the data continuity by plotting the temperature and humidity profiles for all days, a set of gaps in datasets were 93 noticed. Most of the utilized stations have intermittent data gaps of 2-7 days in certain months only but, on the 94 whole, except only a very few cases, the duration of these individual data gaps are mostly limited to less than 1 95 month. However, these small data gaps are not expected to provide any significant impact on the long-term 96 seasonal or annual average variations of 37 years x 12 months span. 97 In addition to the data availability, homogeneity also acts as a common concern before using the data. 98 However, such issues should not be considered serious as all three types of homogeneity issues namely: volume, 99 instrument type and quality have been addressed before commencing the study. First, about 5000 radiosonde 100 profiles are available in majority of IGRA stations which are uniformly distributed among all years and seasons 101 (except monsoon); hence it provides a decent data volume for investigation of yearly trends. Secondly, the data 102 of all Indian IGRA stations come from a single type of IM-MK3 radiosondes which has not undergone any 103 change in radiosonde accuracies in the last years and so this addresses the instrument type related issue.
Load more

Recommended publications
  • Impacts of Anthropogenic Aerosols on Fog in North China Plain
    BNL-209645-2018-JAAM Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE Impacts of Anthropogenic Aerosols on Fog in North China Plain 10.1029/2018JD029437 Xingcan Jia1,2,3 , Jiannong Quan1 , Ziyan Zheng4, Xiange Liu5,6, Quan Liu5,6, Hui He5,6, 2 Key Points: and Yangang Liu • Aerosols strengthen and prolong fog 1 2 events in polluted environment Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing, China, Brookhaven National Laboratory, • Aerosol effects are stronger on Upton, NY, USA, 3Key Laboratory of Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University microphysical properties than of Information Science and Technology, Nanjing, China, 4Institute of Atmospheric Physics, Chinese Academy of Sciences, macrophysical properties Beijing, China, 5Beijing Weather Modification Office, Beijing, China, 6Beijing Key Laboratory of Cloud, Precipitation and • Turbulence is enhanced by aerosols during fog formation and growth but Atmospheric Water Resources, Beijing, China suppressed during fog dissipation Abstract Fog poses a severe environmental problem in the North China Plain, China, which has been Supporting Information: witnessing increases in anthropogenic emission since the early 1980s. This work first uses the WRF/Chem • Supporting Information S1 model coupled with the local anthropogenic emissions to simulate and evaluate a severe fog event occurring Correspondence to: in North China Plain. Comparison of the simulations against observations shows that WRF/Chem well X. Jia and Y. Liu, reproduces the general features of temporal evolution of PM2.5 mass concentration, fog spatial distribution, [email protected]; visibility, and vertical profiles of temperature, water vapor content, and relative humidity in the planetary [email protected] boundary layer throughout the whole period of the fog event.
    [Show full text]
  • GEOGRAPHY OPTIONAL by SHAMIM ANWER
    GEOGRAPHY OPTIONAL by SHAMIM ANWER LEARNING GEOGRAPHY - A NEVER BEFORE EXPERIENCE PREP SUPPLEMENT CLIMA T OLOGY NOT FOR SALE | Off : 57/17 1st Floor, Old Rajender Nagar 8026506054, 8826506099 | Above Dr, Batra’s Delhi - 110060 Also visit us on www.keynoteias.com | www.facebook.com/keynoteias.in KEYNOTE IAS PHYSICAL GEOGRAPHY CLIMATOLOGY INDEX 1. CIRCULATION OF THE ATMOSPHERE ................................................................1-13 Local Winds; Observed Distribution of Pressure and Winds and Idealized Zonal Pressure Belts; Monsoons, Westerlies and Jet Streams; EL Nino and La Nina. 2. MOISTURE AND ATMOSPHERIC STABILITY ..................................................14-24 Atmospheric Stability and Instability 3. FORMS OF CONDENSATION AND PRECIPITATION ........................................25-38 Types and Global Distribution of Precipitation 4. AIR MASSES...........................................................................................................39-53 Polar-Front Theory; Fronts; Cyclone Formation; Cyclonic and Anticyclonic Circulation PREP-SUPPLEMENT: CLIMATOLOGY 1 1. CIRCULATION OF THE ATMOSPHERE Atmospheric circulation and wind Macroscale Winds: The largest wind patterns, called macroscale winds, are exemplified by the Winds are generated by pressure differences that westerlies and trade winds. These planetary-scale arise because of unequal heating of Earth's surface. flow patterns extend around the entire globe and Global winds are generated because the tropics can remain essentially unchanged for weeks at
    [Show full text]
  • Atmospheric Stability Atmospheric Lapse Rate
    ATMOSPHERIC STABILITY ATMOSPHERIC LAPSE RATE The atmospheric lapse rate ( ) refers to the change of an atmospheric variable with a change of altitude, the variable being temperature unless specified otherwise (such as pressure, density or humidity). While usually applied to Earth's atmosphere, the concept of lapse rate can be extended to atmospheres (if any) that exist on other planets. Lapse rates are usually expressed as the amount of temperature change associated with a specified amount of altitude change, such as 9.8 °Kelvin (K) per kilometer, 0.0098 °K per meter or the equivalent 5.4 °F per 1000 feet. If the atmospheric air cools with increasing altitude, the lapse rate may be expressed as a negative number. If the air heats with increasing altitude, the lapse rate may be expressed as a positive number. Understanding of lapse rates is important in micro-scale air pollution dispersion analysis, as well as urban noise pollution modeling, forest fire-fighting and certain aviation applications. The lapse rate is most often denoted by the Greek capital letter Gamma ( or Γ ) but not always. For example, the U.S. Standard Atmosphere uses L to denote lapse rates. A few others use the Greek lower case letter gamma ( ). Types of lapse rates There are three types of lapse rates that are used to express the rate of temperature change with a change in altitude, namely the dry adiabatic lapse rate, the wet adiabatic lapse rate and the environmental lapse rate. Dry adiabatic lapse rate Since the atmospheric pressure decreases with altitude, the volume of an air parcel expands as it rises.
    [Show full text]
  • Atmospheric Thermal and Dynamic Vertical Structures of Summer Hourly Precipitation in Jiulong of the Tibetan Plateau
    atmosphere Article Atmospheric Thermal and Dynamic Vertical Structures of Summer Hourly Precipitation in Jiulong of the Tibetan Plateau Yonglan Tang 1, Guirong Xu 1,*, Rong Wan 1, Xiaofang Wang 1, Junchao Wang 1 and Ping Li 2 1 Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China; [email protected] (Y.T.); [email protected] (R.W.); [email protected] (X.W.); [email protected] (J.W.) 2 Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province, Institute of Plateau Meteorology, China Meteorological Administration, Chengdu 610072, China; [email protected] * Correspondence: [email protected]; Tel.: +86-27-8180-4913 Abstract: It is an important to study atmospheric thermal and dynamic vertical structures over the Tibetan Plateau (TP) and their impact on precipitation by using long-term observation at represen- tative stations. This study exhibits the observational facts of summer precipitation variation on subdiurnal scale and its atmospheric thermal and dynamic vertical structures over the TP with hourly precipitation and intensive soundings in Jiulong during 2013–2020. It is found that precipitation amount and frequency are low in the daytime and high in the nighttime, and hourly precipitation greater than 1 mm mostly occurs at nighttime. Weak precipitation during the daytime may be caused by air advection, and strong precipitation at nighttime may be closely related with air convection. Both humidity and wind speed profiles show obvious fluctuation when precipitation occurs, and the greater the precipitation intensity, the larger the fluctuation. Moreover, the fluctuation of wind speed Citation: Tang, Y.; Xu, G.; Wan, R.; Wang, X.; Wang, J.; Li, P.
    [Show full text]
  • Atmospheric Instability Parameters Derived from Msg Seviri Observations
    P3.33 ATMOSPHERIC INSTABILITY PARAMETERS DERIVED FROM MSG SEVIRI OBSERVATIONS Marianne König*, Stephen Tjemkes, Jochen Kerkmann EUMETSAT, Darmstadt, Germany 1. INTRODUCTION K-Index: Convective systems can develop in a thermo- (Tobs(850)–Tobs(500)) + TDobs(850) – (Tobs(700)–TDobs(700)) dynamically unstable atmosphere. Such systems may quickly reach high altitudes and can cause severe Lifted Index: storms. Meteorologists are thus especially interested to Tobs - Tlifted from surface at 500 hPa identify such storm potentials when the respective system is still in a preconvective state. A number of Maximum buoyancy: obs(max betw. surface and 850) obs(min betw. 700 and 300) instability indices have been defined to describe such Qe - Qe situations. Traditionally, these indices are taken from temperature and humidity soundings by radiosondes. As (T is temperature, TD is dewpoint temperature, and Qe radiosondes are only of very limited temporal and is equivalent potential temperature, numbers 850, 700, spatial resolution there is a demand for satellite-derived 300 indicate respective hPa level in the atmosphere) indices. The Meteorological Product Extraction Facility (MPEF) for the new European Meteosat Second and the precipitable water content as additionally Generation (MSG) satellite envisages the operational derived parameter. derivation of a number of instability indices from the brightness temperatures measured by certain SEVIRI 3. DESCRIPTION OF ALGORITHMS channels (Spinning Enhanced Visible and Infrared Imager, the radiometer onboard MSG). The traditional 3.1 The Physical Retrieval physical approach to this kind of retrieval problem is to infer the atmospheric profile via a constrained inversion An iterative solution to the inversion equation (e.g. and compute the indices then directly from the obtained Ma et al.
    [Show full text]
  • Static Stability (I) the Concept of Stability (Ii) the Parcel Technique (A
    ATSC 5160 – supplement: static stability Static stability (i) The concept of stability The concept of (local) stability is an important one in meteorology. In general, the word stability is used to indicate a condition of equilibrium. A system is stable if it resists changes, like a ball in a depression. No matter in which direction the ball is moved over a small distance, when released it will roll back into the centre of the depression, and it will oscillate back and forth, until it eventually stalls. A ball on a hill, however, is unstably located. To some extent, a parcel of air behaves exactly like this ball. Certain processes act to make the atmosphere unstable; then the atmosphere reacts dynamically and exchanges potential energy into kinetic energy, in order to restore equilibrium. For instance, the development and evolution of extratropical fronts is believed to be no more than an atmospheric response to a destabilizing process; this process is essentially the atmospheric heating over the equatorial region and the cooling over the poles. Here, we are only concerned with static stability, i.e. no pre-existing motion is required, unlike other types of atmospheric instability, like baroclinic or symmetric instability. The restoring atmospheric motion in a statically stable atmosphere is strictly vertical. When the atmosphere is statically unstable, then any vertical departure leads to buoyancy. This buoyancy leads to vertical accelerations away from the point of origin. In the context of this chapter, stability is used interchangeably
    [Show full text]
  • Analysis of Stability Parameters in Relation to Precipitation Associated with Pre-Monsoon Thunderstorms Over Kolkata, India
    Analysis of stability parameters in relation to precipitation associated with pre-monsoon thunderstorms over Kolkata, India H P Nayak and M Mandal∗ Centre for Oceans, Rivers, Atmosphere and Land Sciences, Indian Institute of Technology Kharagpur, Kharagpur 721 302, India ∗Corresponding author. e-mail: [email protected] The upper air RS/RW (Radio Sonde/Radio Wind) observations at Kolkata (22.65N, 88.45E) during pre- monsoon season March–May, 2005–2012 is used to compute some important dynamic/thermodynamic parameters and are analysed in relation to the precipitation associated with the thunderstorms over Kolkata, India. For this purpose, the pre-monsoon thunderstorms are classified as light precipitation (LP), moderate precipitation (MP) and heavy precipitation (HP) thunderstorms based on the magnitude of associated precipitation. Richardson number in non-uniformly saturated (Ri*) and saturated atmosphere (Ri); vertical shear of horizontal wind in 0–3, 0–6 and 3–7 km atmospheric layers; energy-helicity index (EHI) and vorticity generation parameter (VGP) are considered for the analysis. The instability measured ∗ in terms of Richardson number in non-uniformly saturated atmosphere (Ri ) well indicate the occurrence of thunderstorms about 2 hours in advance. Moderate vertical wind shear in lower troposphere (0–3 km) and weak shear in middle troposphere (3–7 km) leads to heavy precipitation thunderstorms. The wind shear in 3–7 km atmospheric layers, EHI and VGP are good predictors of precipitation associated with thunderstorm. Lower tropospheric wind shear and Richardson number is a poor discriminator of the three classified thunderstorms. 1. Introduction high socio-economic impact, thunderstorms are of serious concern to researchers and meteorologists.
    [Show full text]
  • Subseasonal and Diurnal Variability in Lightning and Storm Activity Over the Yangtze River Delta, China, During Mei-Yu Season
    15 JUNE 2020 Y A N G E T A L . 5013 Subseasonal and Diurnal Variability in Lightning and Storm Activity over the Yangtze River Delta, China, during Mei-yu Season a,b,c a,b d,e a,b c JI YANG, KUN ZHAO, XINGCHAO CHEN, ANNING HUANG, YUANYUAN ZHENG, AND a,b,c KANGYUAN SUN a Key Laboratory for Mesoscale Severe Weather/Ministry of Education and School of Atmospheric Science, Nanjing University, Nanjing, China b State Key Laboratory of Severe Weather and Joint Center for Atmospheric Radar Research of the China Meteorological Administration and Nanjing University, Beijing, China c Jiangsu Research Institute of Meteorological Sciences, Nanjing, China d Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania e Center for Advanced Data Assimilation and Predictability Techniques, The Pennsylvania State University, University Park, Pennsylvania (Manuscript received 20 June 2019, in final form 16 March 2020) ABSTRACT Using 5 years of operational Doppler radar, cloud-to-ground (CG) lightning observations, and National Centers for Environmental Prediction reanalysis data, this study examined the spatial and temporal char- acteristics of and correlations between summer storm and lightning activity over the Yangtze River Delta (YRD), with a focus on subseasonal variability and diurnal cycles. The spatiotemporal features of storm top, duration, maximum reflectivity, size, and cell-based vertical integrated liquid water were investigated using the Storm Cell Identification and Tracking algorithm. Our results revealed that there was high storm activity over the YRD, with weak diurnal variations during the mei-yu period. Specifically, storms were strongly associated with mei-yu fronts and exhibited a moderate size, duration, and intensity.
    [Show full text]
  • Teaching Weather and Climate Buoyancy and Vertical Motion Scott
    Teaching Weather and Climate Buoyancy and Vertical Motion Thermodynamics, Buoyancy, and Vertical Motion Temperature, Pressure, and Density Buoyancy and Static Stability Adiabatic “Lapse Rates” Dry and Moist Convective Motions Present Atmospheric Composition What is Air Temperature? • Temperature is a measure of the kinetic (motion) energy of air molecules – K.E. = ½ mv2 m = mass, v = velocity – So…temperature is a measure of air molecule speed • The sensation of warmth is created by air molecules striking and bouncing off your skin surface – The warmer it is, the faster molecules move in a random fashion and the more collisions with your skin per unit time Scott Denning CSU CMMAP 1 Teaching Weather and Climate Buoyancy and Vertical Motion Temperature Scales • In the US, we use Fahrenheit most often • Celsius (centigrade) is a scale based on freezing/boiling of water • Kelvin is the “absolute” temperature scale How do we measure temperature? • Conventional thermometry - Liquid in glass. • Electronic thermometers - Measures resistance in a metal such as nickel. • Remote sensing using radiation emitted by the air and surface (by satellites or by you in this class!). What is the coldest possible temperature? Why? Atmospheric Soundings Helium-filled weather balloons are released from over 1000 locations around the world every 12 hours (some places more often) These document temperature, pressure, humidity, and winds aloft Scott Denning CSU CMMAP 2 Teaching Weather and Climate Buoyancy and Vertical Motion Pressure • Pressure is defined as a force applied per unit area • The weight of air is a force, equal to the mass m times the acceleration due to gravity g • Molecules bumping into an object also create a force on that object, or on one another • Air pressure results from the weight of the entire overlying column of air! How do we measure pressure? Sea Level Value Units of Pressure: (average) 1 atmosphere 760 mm.
    [Show full text]
  • Sea Surface Temperature–Precipitation Relationship in Different Reanalyses
    1118 MONTHLY WEATHER REVIEW VOLUME 141 Sea Surface Temperature–Precipitation Relationship in Different Reanalyses ARUN KUMAR Climate Prediction Center, NOAA/NWS/NCEP, College Park, Maryland LI ZHANG Climate Prediction Center, NOAA/NWS/NCEP, College Park, Maryland, and Wyle Science, Technology, and Engineering, McLean, Virginia WANQIU WANG Climate Prediction Center, NOAA/NWS/NCEP, College Park, Maryland (Manuscript received 2 August 2012, in final form 22 November 2012) ABSTRACT The focus of this investigation is how the relationship at intraseasonal time scales between sea surface temperature and precipitation (SST–P) varies among different reanalyses. The motivation for this work was spurred by a recent report that documented that the SST–P relationship in Climate Forecast System Re- analysis (CFSR) was much closer to that in the observation than it was for the older generation of reanalyses [i.e., NCEP–NCAR reanalysis (R1) and NCEP–Department of Energy (DOE) reanalysis (R2)]. Further, the reason was attributed either to the fact that the CFSR is a partially coupled reanalysis, while R1 and R2 are atmospheric-alone reanalyses, or that R1 and R2 use the observed weekly-averaged SST. The authors repeated the comparison of the SST–P relationship among R1, R2, and CFSR, as well as two recent generations of atmosphere-alone reanalyses, the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and the ECMWF Re-Analysis Interim (ERA-Interim). The results clearly demonstrate that the differences in the SST–P relationship at intraseasonal time scales across different reanalyses are not due to whether the reanalysis system is coupled or atmosphere alone, but are due to the specification of different SSTs.
    [Show full text]
  • Atmospheric Instability As a Loss of a Metastable Equilibrium
    Atmospheric instability as a loss of a metastable equilibrium Yuri Kornyushin Maître Jean Brunschvig Research Unit, Chalet Shalva, Randogne, CH-3975 Abstract. General thermodynamic theory of metastable states is used in this short note to try to understand better atmospheric instabilities. It is shown that not only cooling of a cloud can lead to rain, but heating also, especially when there are charged water drops in a cloud (in this case we have rain with lightning). The influence of the global warming on weather is discussed. 1. Introduction Metastable state in Classical Mechanics is a very well known one and it is shown on Fig. 1, which presents a schematic dependence of mechanical energy E on some parameter X (generalized coordinate). Metastable state (1) exists in a shallow minimum of mechanical energy. It is separated from more stable state (3) by a relatively low barrier (2). As the barrier is relatively low, the equilibrium in position (1) can be easily unstable. Fig. (1). Metastable state (1) in a shallow minimum of the energy in Classical Mechanics. It is separated from more stable state (3) by rather low barrier (2). Parameter X represents some generalized coordinate. Metastable states in Classical Thermodynamics were very well known quite a long time ago (see, e.g. [1]). The specific feature of the metastable state in Classical Thermodynamics is that there exists some virtual critical point (temperature of the absolute instability), Ti. At this temperature the thermodynamic barrier, separating a metastable state from more stable one, does not exist. The matter is that the height of the barrier mentioned depends on temperature, T, and ceases to exist at T = Ti (see, e.g., [2,3]).
    [Show full text]
  • Clouds and Atmospheric Convection
    Clouds and atmospheric convection Caroline Muller CNRS/Laboratoire de Météorologie Dynamique (LMD) Département de Géosciences ENS 1 M2 P7/ IPGP Clouds and atmospheric convection 2 Clouds and atmospheric convection 3 Clouds and atmospheric convection Intertropical Convergence Zone 4 Clouds and atmospheric convection 1. Cloud types 2. Moist thermodynamics and stability 3. Coupling with circulation 5 1. Cloud types Cumulus: heap, pile Stratus: flatten out, cover with a layer Cirrus: lock of hair, tuft of horsehair Combined to define 10 cloud types Nimbus: precipitating cloud Altum: height 6 1. Cloud types Clouds are classified according to height of cloud base and appearance High clouds Base: 5 to 12km Middle clouds Base: 2 to 6km Low clouds Base < 2km 7 1. High Clouds Almost entirely ice crystals Cirrus Wispy, feathery Cirrocumulus Layered clouds, cumuliform lumpiness Cirrostratus Widespread, sun/moon halo 8 1. Middle Clouds Liquid water droplets, ice crystals, or a combination of the two, including supercooled droplets (i.e., liquid droplets whose temperatures are below freezing). Altocumulus Heap-like clouds with convective elements in mid levels May align in rows or streets of clouds Altostratus Flat and uniform type texture in mid levels 9 1. Low Clouds Liquid water droplets or even supercooled droplets, except during cold winter storms when ice crystals (and snow) comprise much of the clouds. The two main types include stratus, which develop horizontally, and cumulus, which develop vertically. Stratocumulus Hybrids of layered stratus and cellular cumulus Stratus Uniform and flat, producing a gray layer of cloud cover Nimbostratus Thick, dense stratus or stratocumulus clouds producing steady rain or snow 10 1.
    [Show full text]